Prognostic value of the Epidural Spinal Cord Compression scale, Revised Tokuhashi, and Spine Instability Neoplastic Scores in primary stereotactic body radiotherapy for spinal bone metastases.
Chou KN, Park DJ, Hori YS, Persad AR, Chuang C, Emrich SC (+6 more)
Abstract
ObjectiveStereotactic body radiotherapy (SBRT) has emerged as a highly effective, noninvasive treatment for spinal bone metastases (SBMs). However, long-term outcomes of primary SBRT and the comparative prognostic performance of commonly used decision-making tools remain incompletely defined. This study evaluated long-term local control (LC) and systematically compared the predictive value of the Epidural Spinal Cord Compression (ESCC) grade, Spine Instability Neoplastic Score (SINS), and revised Tokuhashi score (rTS).MethodsThe authors retrospectively analyzed 330 patients with 537 SBMs treated with primary CyberKnife SBRT between 2012 and 2023. SBMs with surgical indications under the NOMS (neurological, oncological, mechanical, and systemic) framework, defined as high-grade epidural compression (ESCC grade 2 or 3) and/or spinal instability (SINS > 12), were excluded. LC was defined as absence of radiographic tumor regrowth ≥ 6 months post-SBRT. Cox proportional hazards models identified independent predictors of local progression (LP). Prognostic discrimination of the ESCC grade, SINS, rTS, and a novel integrated multivariable model was evaluated using receiver operating characteristic (ROC) analysis.ResultsThe 1- and 2-year LC rates were 86.2% and 75.9%, respectively, with a median time to LP of 12 months. Independent predictors of LP included radioresistant histology, epidural compression, pain, osteolytic destruction, single-fraction equivalent dose ConclusionsPrimary SBRT for SBMs provided durable LC with acceptable toxicity. Although the ESCC grade, SINS, and rTS offered moderate prognostic utility, an integrated multivariable model incorporating tumor, anatomical, and clinical factors demonstrated superior predictive accuracy. Comprehensive risk stratification may refine patient selection and optimize SBRT strategies.